code: def test_binary_classifier_0_1_required(self):
      X, y, A = _get_data()
      y = 2 * y
  
      expgrad = ExponentiatedGradient(
          LogisticRegression(),
          constraints=DemographicParity(),
          max_iter=1,
      )
      with pytest.raises(ValueError) as execInfo:
          expgrad.fit(X, y, sensitive_features=(A))
      assert _LABELS_NOT_0_1_ERROR_MESSAGE == execInfo.value.args[0]
  
file_path: fairlearn/test/unit/reductions/exponentiated_gradient/test_exponentiatedgradient_arguments.py
imports: from test.unit.input_convertors import _map_into_single_column, conversions_for_1d, ensure_dataframe, ensure_ndarray
  from test.unit.reductions.conftest import is_invalid_transformation
  import numpy
  import pandas
  import pytest
  from sklearn.linear_model import LogisticRegression
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import StandardScaler
  from fairlearn.reductions import DemographicParity, ErrorRate, ExponentiatedGradient
  from fairlearn.utils._input_validation import _LABELS_NOT_0_1_ERROR_MESSAGE
  from .simple_learners import LeastSquaresBinaryClassifierLearner
  from .test_utilities import _get_data
label_desc: Use image node_id 4 for calling the TestExponentiatedGradientArguments obj's underlying member method code with example usage: obj.test_binary_classifier_0_1_required() without return types